---
title: Embeddings Overview
sidebarTitle: Overview
description: Overview of the different embeddings available in Chonkie
icon: brain-circuit
iconType: solid
---

Chonkie provides a variety of embeddings handlers to handle different embedding models in a consistent manner.
Embeddings handlers are used in conjunction with chunkers to embed chunks of text. 
Only few chunkers require embeddings, see the [Chunkers Overview](/chunkers/overview) for more information.

## Installation

Embeddings handlers require additional dependencies. See the [Installation Guide](/getting-started/installation) for more information.

<Info>
    By default, Chonkie `semantic` installation includes `Model2VecEmbeddings`, which is the current default embeddings handler
</Info>

## Available Embeddings

<CardGroup cols={2}>
    <Card title="AutoEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/auto-embeddings">
        Automatically select the best embeddings handler for your use case.
    </Card>
    <Card title="CohereEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/cohere-embeddings">
        Embed text using Cohere embeddings (requires `cohere`).
    </Card>
    <Card title="SentenceTransformerEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/sentence-transformer-embeddings">
        Embed text using SentenceTransformer embeddings (requires `sentence-transformers`).
    </Card>
    <Card title="OpenAIEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/openai-embeddings">
        Embed text using OpenAI embeddings (requires `openai`). 
    </Card>
    <Card title="Model2VecEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/model2vec-embeddings">
        Embed text using Model2Vec embeddings (requires `model2vec`).
    </Card>
    <Card title="GeminiEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/gemini-embeddings">
        Embed text using Google Gemini embeddings (requires `google-genai`).
    </Card>
    <Card title="JinaEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/jina-embeddings">
        Embed text using JinaAI embeddings (requires `jina`).
    </Card>
    <Card title="AzureOpenAIEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/azure-embeddings">
        Embed text using Azure OpenAI embeddings (requires `openai`, `azure-identity`).
    </Card>
    <Card title="VoyageAIEmbeddings" icon="brain-circuit" href="/python-sdk/embeddings/voyageai-embeddings">
        Embed text using VoyageAI embeddings (requires `voyageai`).
    </Card>
</CardGroup>

## Common Interface

All embeddings handlers share a consistent interface:

```python
# Single text embedding
emb = embeddings.embed(text)

# Batch processing
emb = embeddings.embed_batch(texts)

# Direct calling
emb = embeddings(text)  # or embeddings([text1, text2])
```